Evidence (16496 claims)
Search and filter individual claims pulled from the papers. Looking for a specific finding ("what's the effect on wages?"), you're in the right place. Want to compare whole outcome categories against each other instead? Use the Evidence Explorer.
The board below groups claims two ways: by broad theme (nine paper-level topics) and by outcome category (the 34 claim-level outcomes that the Explorer and Syntheses also use).
Browse by theme
Nine broad, paper-level topics. Click one to filter the claims below.
Adoption
9875 claims
Filter claims →
Productivity
8807 claims
Filter claims →
Governance
7870 claims
Filter claims →
Human-AI Collaboration
7560 claims
Filter claims →
Org Design
4892 claims
Filter claims →
Innovation
4781 claims
Filter claims →
Labor Markets
4004 claims
Filter claims →
Skills & Training
3308 claims
Filter claims →
Inequality
2332 claims
Filter claims →
Claims by outcome category
Counts by direction of finding. These are the same 34 outcome categories the Explorer compares and the Syntheses are written for. A linked row has a published synthesis.
| Outcome | Positive | Negative | Mixed | Null | Total |
|---|---|---|---|---|---|
| Other | 870 | 233 | 116 | 1066 | 2363 |
| Governance & Regulation | 976 | 451 | 218 | 133 | 1809 |
| Organizational Efficiency | 949 | 224 | 144 | 88 | 1416 |
| Technology Adoption Rate | 764 | 287 | 141 | 122 | 1325 |
| Research Productivity | 501 | 152 | 74 | 362 | 1101 |
| Output Quality | 542 | 216 | 69 | 69 | 896 |
| Decision Quality | 387 | 198 | 94 | 54 | 740 |
| Firm Productivity | 513 | 67 | 101 | 27 | 714 |
| AI Safety & Ethics | 249 | 303 | 73 | 36 | 667 |
| Market Structure | 190 | 192 | 134 | 27 | 548 |
| Task Allocation | 243 | 77 | 91 | 36 | 452 |
| Innovation Output | 291 | 33 | 55 | 20 | 401 |
| Skill Acquisition | 206 | 72 | 65 | 21 | 364 |
| Employment Level | 133 | 63 | 115 | 22 | 335 |
| Fiscal & Macroeconomic | 153 | 79 | 52 | 32 | 323 |
| Task Completion Time | 206 | 37 | 12 | 15 | 272 |
| Firm Revenue | 179 | 52 | 29 | 5 | 266 |
| Consumer Welfare | 130 | 76 | 47 | 13 | 266 |
| Inequality Measures | 48 | 137 | 51 | 6 | 242 |
| Worker Satisfaction | 101 | 81 | 25 | 13 | 220 |
| Error Rate | 84 | 110 | 11 | 5 | 210 |
| Wages & Compensation | 98 | 47 | 30 | 10 | 185 |
| Regulatory Compliance | 88 | 73 | 17 | 7 | 185 |
| Automation Exposure | 66 | 64 | 33 | 16 | 182 |
| Team Performance | 105 | 29 | 30 | 11 | 176 |
| Training Effectiveness | 109 | 22 | 14 | 21 | 168 |
| Developer Productivity | 114 | 21 | 14 | 8 | 158 |
| Job Displacement | 12 | 90 | 24 | 1 | 127 |
| Hiring & Recruitment | 57 | 9 | 9 | 5 | 80 |
| Skill Obsolescence | 6 | 56 | 9 | 1 | 72 |
| Social Protection | 43 | 17 | 8 | 2 | 70 |
| Creative Output | 35 | 21 | 9 | 4 | 70 |
| Labor Share of Income | 18 | 21 | 17 | 1 | 57 |
| Worker Turnover | 15 | 16 | — | 4 | 35 |
| Industry | — | — | — | 1 | 1 |
AI brand visibility can be measured, differs by platform, and varies strongly by brand maturity.
Synthesis claim supported by cross-platform/brand analyses reported in the paper (Ranqo dataset across multiple AI engines and >100 brands, March–May 2026); empirical results (tiered visibility, citation patterns) underpin the assertion.
The macroeconomic significance of AI-induced productivity depends not only on technological efficiency, but also on the distributive transmission of productivity gains through labour income, disposable income, prices, investment, public expenditure, transfers and external demand.
Theoretical argument and synthesis of literature in the conceptual review (no new empirical estimation reported).
Returnees face a short-run employment penalty after returning from cross-border work, but this penalty fades with cross-border tenure and with time since return.
Chapter 4: causal analysis using linked Belgian administrative registers comparing returnees to stayers; reported short-run employment penalty and dynamic fade-out with tenure and time since return.
Random-forest models (Belgian administrative registers) reveal sharply nonlinear transition patterns predicting entry and exit into cross-border work, with commuting time, prior employment instability, earnings, and household cross-border exposure as strong predictors.
Chapter 4: linked Belgian administrative registers identifying cross-border spells in Luxembourg; predictive analysis using random-forest models; individual-level predictors and nonlinear patterns reported.
AI-driven technological progress generates localized efficiency improvements while diffusing only weakly across the broader economy.
Synthesis of empirical results: localized positive associations between intangible capital and sectoral productivity versus weak/insignificant associations between AI patent intensity and aggregate TFP (analysis based on OECD Productivity, OECD STAN, INTAN-Invest, OECD Patents, FUAs; panel and robust regressions and descriptive work).
The guarded engagement loop framework conceptualizes generative AI adoption as a feedback process in which risk perceptions may shape interaction conditions that, in turn, can influence observed performance and subsequent trust calibration.
Central conceptual claim of the paper; framework articulated by the authors and presented as a set of testable propositions (theoretical contribution rather than empirical finding in the abstract).
Risk salience may shape interaction dynamics with LLMs via a multilevel feedback mechanism called the 'guarded engagement loop', in which risk perceptions shape interaction strategies that influence observed performance and, in turn, recalibrate trust in generative AI systems.
Conceptual framework proposed by the authors, integrating theories from trust in automation, privacy calculus, algorithm aversion, and social amplification of risk; presented as a theoretical model rather than an empirical test.
LLM guidance was associated with increased pupil size variability.
Physiological eye-tracking measure (pupil size variability) reported and compared across conditions in the simulated SAR experiment.
Eye-tracking data revealed an attention-guidance trade-off: visual resources shifted to the chat interface when LLM guidance was present.
Eye-tracking measures collected during the experiment showing changes in gaze allocation (increased fixations/dwell time on the chat interface) across LLM-guided vs baseline conditions.
The paper formalizes four mechanism theorems explaining the overhead-pressure dynamics: overhead non-additivity, augmentation-saved-time pathways, innovation-premium amplification, and human-AI dyad attribution uncertainty.
Presentation of four mechanism theorems within the paper (theoretical/mathematical exposition rather than direct empirical tests).
The ICH framework predicts three distinct augmentation regimes (determined by combinations of A and C) with distinct policy implications.
Theoretical classification derived from the model; conceptual prediction presented in the paper.
The effect of AI development on firms' labor educational structure is substantially larger in high-technology industries: the effect in high-technology industries is approximately 2.5 times as large as that in non-high-technology industries.
Industry heterogeneity analysis reported in the paper comparing coefficients for high-technology vs. non-high-technology industry subsamples using firm-level data (Chinese A-share firms, 2014–2024); reported ratio ≈ 2.5.
The substitution (for low-educated labor) and complementarity (with high-educated labor) effects of AI on firms' labor educational structure exhibit significant regional heterogeneity: the substitution effect is stronger in developed regions, while the complementarity effect is more pronounced in less developed regions.
Subgroup/heterogeneity analysis across regions using the firm-level panel (Chinese A-share firms, 2014–2024); reported differences in coefficients by regional development level.
Firms' technological innovation capability significantly mediates the effect of AI development on labor educational structure: by enhancing technological innovation capability, AI reduces demand for low-educated labor and increases demand for high-educated labor.
Mediation/causal pathway analysis reported in the study using firm-level data and mediation regressions on Chinese A-share listed firms (2014–2024); the paper reports that technological innovation capability is a significant mediating variable linking AI development to changes in labor education composition.
The empirical tests reported in the study use a sample of agricultural enterprises.
Paper text explicitly frames findings and implications for agricultural enterprises and states empirical tests were conducted on agri-business firms.
AI-induced changes are displacing existing labor jobs while also creating new jobs that require high technological skills.
Summary claim from the SLR reporting that reviewed empirical studies report both displacement of existing jobs and creation of new, high-skill jobs; no quantified displacement/creation rates provided in the excerpt.
Between 2017 and 2025, studies identified current trends of AI-induced changes affecting both blue-collar and white-collar occupations.
Synthesis statement in the paper reporting that reviewed empirical studies identified trends across blue- and white-collar jobs (timeframe 2017–2025). Specific studies or counts not provided in the excerpt.
AI's rapid evolution has profound effects on the labor market, influencing the levels, skills needed for jobs, and overall jobs content.
Statement from the paper's synthesis/introduction summarizing reviewed empirical studies (systematic literature review covering studies from 2017–2025). Number of underlying studies not reported in the excerpt.
While AI has the potential to improve operational efficiency and strengthen adaptive capacity, inadequate readiness can increase systemic risks arising from algorithmic opacity, cybersecurity challenges, data dependence, coordination failures, and disruptions that may spread across interconnected administrative systems.
Conclusion drawn from the integrative conceptual framework and the systematic review of 68 empirical studies documenting both benefits and risks in different contexts.
Evidence on the productivity, risk, and resilience implications of AI adoption remains fragmented and dispersed across different fields of research.
Author's assessment of the literature based on the systematic review (PRISMA) of 68 empirical studies published 2015–2025.
Organisational performance becomes more dependent on the reliability of algorithms, the quality of data, effective governance, and coordination among public institutions.
Conceptual argument supported by synthesis of empirical studies in the systematic review (68 peer-reviewed empirical studies).
Artificial intelligence (AI) is becoming increasingly embedded in the digital infrastructure of local government, creating new opportunities to improve public sector productivity while also influencing systemic risk and organisational resilience across interconnected public systems.
Statement based on literature synthesis in the paper; theoretical framing and review of empirical studies (systematic review).
The paper develops the concept of 'bidirectional dynamics' in digital sovereignties, applying a paradoxical view to interpret institutional control objectives and individual autonomy aspirations as persistent organizational tensions in AI adoption.
Theoretical/conceptual development grounded in the empirical single-case study; concept introduced and motivated by observed tensions in the organization (empirical method details and sample size not provided).
Early digital transformation presents tensions but also synergies between digital sovereignty levels in AI adoption.
Empirical observations from the single-case study of a Nordic public transportation organization during early AI adoption; qualitative examples and analysis (specific methods/sample size not stated).
The relationship between AI use levels and corporate carbon emission intensity exhibits a significant inverted U-shaped curve: at early stages AI adoption may increase emissions, but beyond a critical point further AI use significantly reduces emissions.
Empirical two-way fixed effects (TWFE) analysis on provincial panel data from China, with robustness checks; the paper reports a statistically significant inverted U-shaped relationship.
Embodied intelligence is driving the human-machine relationship from a "human-dominated" model toward "collaborative co-creation," which, while boosting productivity, also triggers deep-seated contradictions in production relations.
Conceptual/theoretical argumentation in the paper, drawing on Marx's theory of reproduction; no empirical sample or quantitative data reported.
The endurance budget is dormant on premium 3,000-P/E TLC at datasheet prices and binding on the commodity QLC/eMMC (~1,000 P/E) that cheaper edge robots run.
Comparative statement based on device endurance specifications cited in the paper (3,000 P/E for TLC vs ~1,000 P/E for QLC/eMMC) and cost/pricing considerations; presented as boundary conditions for when the endurance budget matters. No empirical sample size reported.
Measured on real robot logs, the sign of the value-write association χ is a property of the deployment regime: positive on recurrent long-horizon manipulation (ĥχ ≈ +1.0 × 10^{-3}, replicated at full power), null on a shorter-horizon suite, and negative on non-recurrent teleoperation.
Empirical measurement on real robot logs at a pre-specified gate; reports an estimated value ĥχ ≈ +1.0 × 10^{-3} for recurrent long-horizon manipulation and qualitatively reports null and negative signs for other regimes. The paper states the +1.0e-3 estimate was replicated at full power. Exact sample size not reported in the excerpt.
The index is cost-optimal whatever the sign of the value-write association χ; only when χ > 0 does the optimum turn non-monotone, sending a robot's most valuable memories off its flash.
Theoretical result from the paper's model/analysis. The claim states a general optimality property (index cost-optimal for all χ) and a conditional structural result (non-monotone placement when χ>0). No empirical sample size reported.
Generative engine optimization (GEO) should be studied not only as a security risk, but also as an emerging marketing practice that shapes market competition.
Paper's concluding/interpretive statement based on the experimental findings about LLM recommendation dynamics and GEO effects on brand recommendations.
The near-term value of Agentic AI does not lie in full autonomy or workforce reduction, but in controlled partial autonomy for simple and medium complexity business processes.
Central argumentative claim/recommendation in the paper (theoretical justification; no empirical study or sample size reported).
Quantile regression estimates reveal pronounced asymmetry across the biofuel production distribution: the AI effect is substantially stronger among low-production countries (Q10–Q25 elasticities: 0.58–0.61) and statistically insignificant among high-production countries.
Quantile regression analysis reported in the paper with elasticity estimates for Q10–Q25 and significance tests across quantiles.
The pattern of timing and magnitudes for publication volume and VC investment is theoretically consistent with a multi-stage technology diffusion process, implying two complementary pathways: a research output channel and a commercial adoption channel.
Interpretation based on differential lags and elasticities (2‑year lag for publications vs 1‑year for VC) and theoretical framing in discussion.
This shift raises fundamental questions for consumer theory, which has traditionally modeled humans as the primary decision-makers.
Conceptual argument presented in the paper framing the research problem and motivating the new theoretical framework; literature critique rather than empirical test.
The modality gap (weaker penalty for visual vs. textual AI-use disclosure) widens when AI is used in final products but narrows when AI is used in marketing materials.
Interaction analyses across application stages (final product vs. marketing material) within the 41,073 Kickstarter projects, using LLM-assisted classification to label both modality and application stage and entropy balancing for covariate control.
Panel autoregressive distributed lag estimates reveal strong support for the load capacity curve (LCC) hypothesis, indicating a nonlinear income–environment relationship.
Panel ARDL econometric analysis on G-7 countries over 1990–2019 (authors report use of LCC framework and panel ARDL estimation).
The effectiveness of AI in strategic core functions is contingent upon the human–AI interface.
Stated as a conditional claim in the paper—AI effectiveness depends on the quality of the human–AI interface; no empirical quantification provided in the summary.
Bias transfer from the LLM is asymmetric: agency is suppressed in female-target essays while male-target writing remains largely unaffected.
Comparative analysis within the participant data showing differential effects by target gender (female-target vs male-target essays) in the N = 123 study; reported asymmetry in the paper summary.
A third possibility — the collective and self-organized stewardship of AI-relevant resources by communities (commons-governed approaches) — remains comparatively under-theorized in scholarship even as it proliferates in practice (e.g., data trusts, cooperatives, federated learning consortia, public compute initiatives, open-weight collaborations, community data sovereignty regimes).
Comparative literature review noting fewer theoretical treatments of commons approaches alongside cited examples of practical manifestations (lists of existing initiatives and models).
Tranquil periods lower subjective risk assessments, raise AI substitution intensity, and compound leverage, generating a cognitive Minsky moment in which subjective risk falls while true systemic fragility rises.
Derived dynamics and comparative statics in the formal model; stated as one of the paper's propositions. No empirical data.
Dominant comments shifted in tone from mockery toward gatekeeping and structural protest.
Speech-act coding of 300 confirmed accusations and sentiment/trajectory analysis showing relative decline in mockery-coded acts and increase in gatekeeping/structural-protest acts over time.
The U-shaped pattern is concentrated in software-based AI applications rather than supporting hardware.
Heterogeneity/subgroup analyses in paper that separate software-based AI applications from supporting hardware and find the non-linear pattern concentrated in software applications.
Spline regressions, the Lind–Mehlum U-test, an instrumental-variable analysis using leave-one-out peer AI investment, and entropy balancing all support the non-linear (U-shaped) pattern.
Robustness and identification methods reported in paper: spline regressions, Lind–Mehlum U-test for U-shape, IV using leave-one-out peer AI investment, and entropy balancing.
There is a U-shaped association between AI investment and internal control deficiency (ICD) risk.
Main empirical finding reported in paper based on analyses of 41,725 firm-year observations; supported by spline regressions and Lind–Mehlum U-test.
Technological containment policies may unintentionally accelerate open innovation ecosystems as a competitive response, with implications for global leadership in both academic and commercial artificial intelligence.
Synthesis and inferential claim in the paper drawing on the temporal association of containment measures, policy shifts, developer behavior, diffusion patterns, and patent/research evidence described earlier in the paper.
Across compression sweeps, real factor archives, and LLM-SRBench tasks, hybrid gains concentrate in weakly represented but target-bearing directions and vanish as the hypothesis space approaches full rank.
Empirical claim based on experiments over compression sweeps, analyses of real factor archives (A-share factor discovery), and LLM-SRBench tasks; no numerical sample sizes or effect magnitudes provided in the abstract.
The paper engages six credible objections: commercial pressure and practical feasibility; democratic legitimacy; regulatory compliance; over-reliance on institutionalist explanations; the charge that the floor itself is culturally laden; and the limits of Coherent Extrapolated Volition.
Descriptive claim listing the objections the authors address in the paper; asserted in the abstract as part of paper structure.
The pluralistic-alignment program correctly diagnoses that there is no single 'humanity' to align with, but is dangerous if taken as the main directive.
Analytic claim about the merits and risks of the pluralistic-alignment approach; presented as argumentation rather than empirical result in the abstract.
Human values produce societies that thrive or fail on the merits of those values — from failed states and extreme inequality to declining happiness, political polarization, and government dysfunction in the world's wealthiest democracies.
Descriptive/causal claim asserted by authors linking values to a range of societal outcomes; no specific empirical studies or samples cited in the abstract.
Forms of resistance exist, including localisation efforts and Indigenous ethical frameworks, but they remain structurally limited.
Synthesis of examples and themes across the 50 reviewed articles noting reported resistance strategies and their limits.